Working toward PyPi build

.travis.yml

@@ -0,0 +1,24 @@
+language: python
+sudo: required
+dist: trusty
+
+python:
+    - '2.7'
+    - '3.5'
+    - '3.6'
+
+install:
+    - pip install .
+    - pip install nose2
+
+deploy:
+    provider: pypi
+    user: mmatl
+    on:
+        tags: true
+        branch: master
+    password:
+        secure: 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
+
+notifications:
+    email: false

gqcnn/__init__.py

@@ -1,17 +1,18 @@
-from optimizer_constants import ImageMode, TrainingMode, PreprocMode, InputDataMode, GeneralConstants, ImageFileTemplates
-from train_stats_logger import TrainStatsLogger
-from learning_analysis import ClassificationResult, RegressionResult, ConfusionMatrix
+from .version import __version__
+from .optimizer_constants import ImageMode, TrainingMode, PreprocMode, InputDataMode, GeneralConstants, ImageFileTemplates
+from .train_stats_logger import TrainStatsLogger
+from .learning_analysis import ClassificationResult, RegressionResult, ConfusionMatrix
 
-from neural_networks import GQCNN
-from sgd_optimizer import SGDOptimizer
-from gqcnn_analyzer import GQCNNAnalyzer
+from .neural_networks import GQCNN
+from .sgd_optimizer import SGDOptimizer
+from .gqcnn_analyzer import GQCNNAnalyzer
 
-from grasp import Grasp2D
-from visualizer import Visualizer
-from policy_exceptions import NoValidGraspsException, NoAntipodalPairsFoundException
-from image_grasp_sampler import ImageGraspSampler, AntipodalDepthImageGraspSampler, ImageGraspSamplerFactory
-from policy import Policy, GraspingPolicy, AntipodalGraspingPolicy, CrossEntropyAntipodalGraspingPolicy, QFunctionAntipodalGraspingPolicy, EpsilonGreedyQFunctionAntipodalGraspingPolicy, RgbdImageState, ParallelJawGrasp
-from gqcnn_prediction_visualizer import GQCNNPredictionVisualizer
+from .grasp import Grasp2D
+from .visualizer import Visualizer
+from .policy_exceptions import NoValidGraspsException, NoAntipodalPairsFoundException
+from .image_grasp_sampler import ImageGraspSampler, AntipodalDepthImageGraspSampler, ImageGraspSamplerFactory
+from .policy import Policy, GraspingPolicy, AntipodalGraspingPolicy, CrossEntropyAntipodalGraspingPolicy, QFunctionAntipodalGraspingPolicy, EpsilonGreedyQFunctionAntipodalGraspingPolicy, RgbdImageState, ParallelJawGrasp
+from .gqcnn_prediction_visualizer import GQCNNPredictionVisualizer
 
 __all__ = ['GQCNN', 
            'SGDOptimizer',

gqcnn/experiment_recorder.py

@@ -17,7 +17,6 @@
 
 from autolab_core import CSVModel, ExperimentLogger, YamlConfig
 from autolab_core.utils import gen_experiment_id
-
 from perception import BinaryImage, DepthImage, Image
 
 class LoggerField(object):

gqcnn/gqcnn_analyzer.py

@@ -16,9 +16,8 @@
 import sys
 import time
 
-from gqcnn import GQCNN, ClassificationResult
-
-from optimizer_constants import InputDataMode, ImageMode
+from . import GQCNN, ClassificationResult
+from .optimizer_constants import InputDataMode, ImageMode
 
 binary_im_tf_tensor_template = 'binary_ims_tf'
 depth_im_tf_tensor_template = 'depth_ims_tf'
@@ -388,4 +387,4 @@ def _plot(self):
         handles, labels = plt.gca().get_legend_handles_labels()
         plt.legend(handles, labels, loc='best')
         figname = os.path.join(self.output_dir, 'ROC.pdf')
-        plt.savefig(figname, dpi=self.dpi)
+        plt.savefig(figname, dpi=self.dpi)

gqcnn/gqcnn_prediction_visualizer.py

@@ -13,8 +13,8 @@
 from autolab_core import YamlConfig, Point
 from perception import BinaryImage, ColorImage, DepthImage, GdImage, GrayscaleImage, RgbdImage, RenderMode
 
-from gqcnn import Grasp2D, GQCNN, ClassificationResult, InputDataMode, ImageMode, ImageFileTemplates
-from gqcnn import Visualizer as vis2d
+from . import Grasp2D, GQCNN, ClassificationResult, InputDataMode, ImageMode, ImageFileTemplates
+from . import Visualizer as vis2d
 
 import IPython
 

gqcnn/image_grasp_sampler.py

@@ -23,10 +23,10 @@
 from autolab_core import Point, RigidTransform
 from perception import BinaryImage, ColorImage, DepthImage, RgbdImage
 
-from gqcnn import Grasp2D
-from gqcnn import Visualizer as vis
+from . import Grasp2D
+from . import Visualizer as vis
 
-from gqcnn import NoAntipodalPairsFoundException
+from . import NoAntipodalPairsFoundException
 
 def force_closure(p1, p2, n1, n2, mu):
     """ Computes whether or not the point and normal pairs are in force closure. """